# CMU 11-785: Introduction to Deep Learning

## Descriptions

- Offered by: CMU
- Prerequisites: Linear Algebra, Probability, Python Programming, and ML Foundations
- Programming Languages: Python
- Difficulty: 🌟🌟🌟🌟🌟
- Class Hour: ~120 hours

CMU 11-785 is a rigorous, fast-paced deep learning core course with very little filler. It starts from neural network fundamentals and systematically covers CNNs, RNNs, Attention/Transformers, optimization, and generalization.

The workload feels close to graduate-level training: assignments usually require real understanding of model behavior, training details, and experimental methodology. If you want durable deep learning fundamentals (instead of only using high-level APIs), this course is an excellent investment.

## Course Resources

- Course Website: <https://deeplearning.cs.cmu.edu/S26/index.html>
- Recordings: Lecture recordings are available on course websites (varies by semester)
- Textbooks: Mainly Lecture Notes / Slides + paper readings
- Assignments: Multiple programming assignments and a course project (published on course sites)

## Personal Resources

No public personal repository is currently provided for this course.
